Artificial intelligence, as abbreviated as AI, is a new technical science for researching and developing theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. Artificial intelligence is a branch of computer science and attempts to learn about the essence of intelligence, and produce a new intelligent machine capable of responding in a manner similar to human intelligence. The studies in the field comprise robots, language recognition, image recognition, natural language processing, expert systems and the like.
Named Entity Recognition (NER) is a sequence labelling task in Natural Language Processing (NLP). The sequence labelling refers to endowing a certain label to each symbol in the sequence, and mainly employs an implementation mode of statistics plus rules. The Named Entity Recognition may labels entities in a query according to classes such as person name, place name and time.
In practical application, it is necessary to look up to find situations of bad cases to perform optimized update for a Named Entity Recognition system.
In the prior art, situations of bad cases are mainly looked up and found in a manner of a person's operation, i.e., a person randomly samples recognition results of the Named Entity Recognition system, and reviews and analyzes the sampled recognition results to determine whether there are bad cases.
The above manner at least has the following problems: since operations need to be performed by a person, very high man power costs are needed and a processing efficiency is low. In addition, since random sampling is performed, all bad cases might not be found, i.e., a discovery rate of bad cases is very low, thereby affecting subsequent optimization and update of the named entity recognition system.